Feb 3, 2021 · We study the task of sentence-level argument mining, as arguments mostly require some degree of world knowledge to be identified and understood.
Feb 3, 2021 · This paper presents a hybrid model that combines latent Dirichlet allocation and word embeddings to obtain external knowledge from ...
Oct 27, 2020 · This chapter presents the investigated strategies for property selection via topic mod- eling, efficient structured knowledge retrieval via word ...
This paper focuses on two steps of decision-making: extracting evidence by building knowledge graphs (KGs) of specialized topics and identifying sentences' ...
We use a topic model to extract topic- and sentence-specific evidence from the structured knowledge base Wikidata, building a graph based on the cosine ...
Thesis. Focusing knowledge-based graph argument mining via topic modeling. Requirements. Python 3.6 for the classifier, run. py -3.6 -m pip install -r ...
Feb 3, 2021 · We use a topic model to extract topic- and sentence-specific evidence from the struc- tured knowledge base Wikidata, building a graph based on ...
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What is topic modelling in text mining?
What is knowledge based graph?
This paper develops topic modeling with knowl- edge graph embedding (TMKGE), a hierarchical. Dirichlet process (HDP) based model to extract more coherent topics ...
We use a topic model to extract topic- and sentence-specific evidence from the structured knowledge base Wikidata, building a graph based on the cosine ...
This paper focuses on two steps of decision-making: extracting evidence by building knowledge graphs (KGs) of specialized topics and identifying sentences' ...